Refund Radar

Scan bank statements to detect recurring charges, flag suspicious transactions, and draft refund requests with interactive HTML reports.

Scan bank statements to detect recurring charges, flag suspicious transactions, identify duplicates and fees, draft refund request templates, and generate an interactive HTML audit report.

Triggers

• "scan my bank statement for refunds"
• "analyze my credit card transactions"
• "find recurring charges in my statement"
• "check for duplicate or suspicious charges"
• "help me dispute a charge"
• "generate a refund request"
• "audit my subscriptions"

Workflow

1. Get Transaction Data

Ask user for bank/card CSV export or pasted text. Common sources:

• Apple Card: Wallet → Card Balance → Export
• Chase: Accounts → Download activity → CSV
• Mint: Transactions → Export
• Any bank: Download as CSV from transaction history

Or accept pasted text format:

text

2026-01-03 Spotify -11.99 USD
2026-01-15 Salary +4500 USD

2. Parse and Normalize

Run the parser on their data:

bash

python -m refund_radar analyze --csv statement.csv --month 2026-01

Or for pasted text:

bash

python -m refund_radar analyze --stdin --month 2026-01 --default-currency USD

The parser auto-detects:

• Delimiter (comma, semicolon, tab)
• Date format (YYYY-MM-DD, DD/MM/YYYY, MM/DD/YYYY)
• Amount format (single column or debit/credit)
• Currency

3. Review Recurring Charges

Tool identifies recurring subscriptions by:

• Same merchant >= 2 times in 90 days
• Similar amounts (within 5% or $2)
• Consistent cadence (weekly, monthly, yearly)
• Known subscription keywords (Netflix, Spotify, etc.)

Output shows:

• Merchant name
• Average amount and cadence
• Last charge date
• Next expected charge

4. Flag Suspicious Charges

Tool automatically flags:

Flag Type	Trigger	Severity
Duplicate	Same merchant + amount within 2 days	HIGH
Amount Spike	> 1.8x baseline, delta > $25	HIGH
New Merchant	First time + amount > $30	MEDIUM
Fee-like	Keywords (FEE, ATM, OVERDRAFT) + > $3	LOW
Currency Anomaly	Unusual currency or DCC	LOW

5. Clarify with User

For flagged items, ask in batches of 5-10:

• Is this charge legitimate?
• Should I mark this merchant as expected?
• Do you want a refund template for this?

Update state based on answers:

bash

python -m refund_radar mark-expected --merchant "Costco"
python -m refund_radar mark-recurring --merchant "Netflix"

6. Generate HTML Report

Report saved to ~/.refund_radar/reports/YYYY-MM.html

Copy template.html structure. Sections:

• Summary: Transaction count, total spent, recurring count, flagged count
• Recurring Charges: Table with merchant, amount, cadence, next expected
• Unexpected Charges: Flagged items with severity and reason
• Duplicates: Same-day duplicate charges
• Fee-like Charges: ATM fees, FX fees, service charges
• Refund Templates: Ready-to-copy email/chat/dispute messages

Features:

• Privacy toggle (blur merchant names)
• Dark/light mode
• Collapsible sections
• Copy buttons on templates
• Auto-hide empty sections

7. Draft Refund Requests

For each flagged charge, generate three template types:

• Email: Formal refund request
• Chat: Quick message for live support
• Dispute: Bank dispute form text

Three tone variants each:

• Concise (default)
• Firm (assertive)
• Friendly (polite)

Templates include:

• Merchant name and date
• Charge amount
• Dispute reason based on flag type
• Placeholders for card last 4, reference number

Important: No apostrophes in any generated text.

CLI Reference

bash

# Analyze statement
python -m refund_radar analyze --csv file.csv --month 2026-01

# Analyze from stdin
python -m refund_radar analyze --stdin --month 2026-01 --default-currency CHF

# Mark merchant as expected
python -m refund_radar mark-expected --merchant "Amazon"

# Mark merchant as recurring
python -m refund_radar mark-recurring --merchant "Netflix"

# List expected merchants
python -m refund_radar expected

# Reset learned state
python -m refund_radar reset-state

# Export month data
python -m refund_radar export --month 2026-01 --out data.json

Files Written

Path	Purpose
~/.refund_radar/state.json	Learned preferences, merchant history
~/.refund_radar/reports/YYYY-MM.html	Interactive audit report
~/.refund_radar/reports/YYYY-MM.json	Raw analysis data

Privacy

• No network calls. Everything runs locally.
• No external APIs. No Plaid, no cloud services.
• Your data stays on your machine.
• Privacy toggle in reports. Blur merchant names with one click.

Requirements

• Python 3.9+
• No external dependencies

Repository

https://github.com/andreolf/refund-radar